System and method for determining a behavior of a classifier for use with business data

Abstract

A method for detecting change in business data using a statistical classifier process. The method includes inputting a first set of business data in a first format from a real business process from a first data source and storing the first set of business data into one or more memories. The method also includes inputting a second set of business data in a second format from a real business process from a second data source and storing the second set of business data into one or more memories. The method forms a statistical classifier by inputting the first set of business data into a learning process associating with the statistical classifier that processes business the data in the first format. The method stores the classifier into the one or more memories, the classifier being associated with the first set of data in the first format and processes the data from the first data source in the statistical classifier to derive a first result. The method also processes the data from the second data source in the statistical classifier to derive a second result and determines a behavior of the statistical classifier based upon at least the first result and the second result. The method displays information associated with the behavior of the statistical classifier.

Description

CROSS REFERENCE TO RELATED APPLICATIONS [0001] This application claims priority to U.S. Provisional Application No.60 / 490,219 entitled “SYSTEM AND METHOD FOR EFFICIENT ENRICHMENT OF BUSINESS DATA”, and filed on Jul. 25, 2003 (Attorney Docket No. 021269-000500US), and incorporated herein by reference.BACKGROUND OF THE INVENTION [0002] The present invention relates generally to supporting business decisions through data analysis by way of enriching data through data mining, text mining, and automatic classification. More particularly, the invention provides a method and system for 1) automatic detection of change in the business processes to be analyzed; 2) accurate measurement of the performance of automatic classification of business process data; 3) automatic handling of semi-structured text in business process analysis; and 4) efficient and maintainable scripting of the data enrichment process. Business decisions generally require knowledge about properties of business entities re...

AI Technical Summary

Benefits of technology

[0008] According to the present invention, techniques for supporting business decisions through data analysis by way of enriching data through data mining, text mining, and automatic classification are provided. More particularly, the invention provides a method and system for 1) automatic detection of change in the business processes to be analyzed; 2) accurate measurement of the performance of automatic classification of business process data; 3) automatic handling of semi-structured text in business process analysis; and 4) efficient and maintainable scripting of the data enrichment process. Business decisions generally require knowledge about properties of business entities related to the decision. Such properties can be inferred by an automatic classifier that processes data associated with the entity. Parts of the data may be human-generated or free form text. Other parts of the data may be machine-generated or semi-structured. It is beneficial to analyze both free form text and semi-structured text data for business process analysis. While the enrichment process can be programmed in a number of existing programming languages and data base query languages, it is advantageous to provide a specialized language for increased maintainability and faster development of the enrichment process. By way of example for the enabling features of such a language, we describe SQXML, a language developed by Enkata Technologies, Inc. for this purpose. The business decision can relate to marketing, sales, procurement, operations, or any other business area that generates and captures real data in electronic form. Merely by way of example, the invention is applied to processing data from a call center of a large wireless telecommunication service provider. But it would be recognized that the invention has a much wider range of applicability. For example, the invention can be applied to other operational and non-operational business areas such as manufacturing, financial services, insurance services, high technology, retail, consumer products, and the like.

Problems solved by technology

Companies spent considerable time and effort to control costs to improve profits and operations.

Unfortunately, conventional techniques for analyzing such information are often time consuming and not efficient.

That is, such techniques are often manual and require much effort.

Accordingly, companies are often unable to identify certain business improvement opportunities.

Much of the raw data including voice and free-form text data are in unstructured form thereby rendering the data almost unusable to traditional analytical software tools.

Unfortunately, certain limitations still exist.

Such statistical classifiers often become inaccurate over time and must be reformed.

Conventional techniques for reforming statistical classifiers are often cumbersome and difficult to perform.

Although these techniques have had certain success, there are many limitations.

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